plsdof (version 0.2-1)

pls.dof: Computation of the Degrees of Freedom

Description

This function computes the Degrees of Freedom using the Krylov representation of PLS.

Usage

pls.dof(pls.object,n,y,K,m,DoF.max)

Arguments

pls.object

object returned by linear.pls.fit or by kernel.pls.fit

n

number of observations

y

vector of response observations.

K

kernel matrix X X^t.

m

number of components

DoF.max

upper bound on the Degrees of Freedom.

Value

• coefficients
  matrix of regression coefficients
• intercept
  vector of regression intercepts
• DoF
  Degrees of Freedom
• sigmahat
  vector of estimated model error
• Yhat
  matrix of fitted values
• yhat
  vector of squared length of fitted values
• RSS
  vector of residual sum of error
• TT
  matrix of normalized PLS components

Details

to do.

References

Kraemer, N., Sugiyama M. (2010). "The Degrees of Freedom of Partial Least Squares Regression". preprint, http://arxiv.org/abs/1002.4112 Kraemer, N., Sugiyama M., Braun, M.L. (2009) "Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression." Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS), p. 272-279

See Also

pls.model, pls.ic

Examples

# this is an internal function